 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8R418 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MKSPALQPLSMAGLQLMTPASSPMGPFFGLPWQQEAIHDNIYTPRKYQVE 50
51 LLEAALDHNTIVCLNTGSGKTFIAVLLTKELAHQIRGDLNPHAKRTVFLV 100
101 NSANQVAQQVSAVRTHSDLKVGEYSDLEVNASWTKERWSQEFTKHQVLIM 150
151 TCYVALTVLKNGYLSLSDINLLVFDECHLAILDHPYREIMKLCESCPSCP 200
201 RILGLTASILNGKCDPEELEEKIQKLERILRSDAETATDLVVLDRYTSQP 250
251 CEIVVDCGPFTDRSGLYERLLMELEAALDFINDCNVAVHSKERDSTLISK 300
301 QILSDCRAVLVVLGPWCADKVAGMMVRELQKYIKHEQEELHRKFLLFTDT 350
351 LLRKIHALCEEYFSPASLDLKYVTPKVMKLLEILRKYKPYERQQFESVEW 400
401 YNNRNQDNYVSWSDSEDDDDDEEIEEKEKPETNFPSPFTNILCGIIFVER 450
451 RYTAVVLNRLIKEAGKQDPELAYISSNFITGHGIGKNQPRSKQMEAEFRK 500
501 QEEVLRKFRAHETNLLIATSVVEEGVDIPKCNLVVRFDLPTEYRSYVQSK 550
551 GRARAPISNYVMLADTDKIKSFEEDLKTYKAIEKILRNKCSKSADGAEAD 600
601 VHAGVDDEDAFPPYVLRPDDGGPRVTINTAIGHINRYCARLPSDPFTHLA 650
651 PKCRTRELPDGTFYSTLYLPINSPLRASIVGPPMDSVRLAERVVALICCE 700
701 KLHKIGELDEHLMPVGKETVKYEEELDLHDEEETSVPGRPGSTKRRQCYP 750
751 KAIPECLRESYPKPDQPCYLYVIGMVLTTPLPDELNFRRRKLYPPEDTTR 800
801 CFGILTAKPIPQIPHFPVYTRSGEVTISIELKKSGFTLSQQMLELITRLH 850
851 QYIFSHILRLEKPALEFKPTGAESAYCVLPLNVVNDSGTLDIDFKFMEDI 900
901 EKSEARIGIPSTKYSKETPFVFKLEDYQDAVIIPRYRNFDQPHRFYVADV 950
951 YTDLTPLSKFPSPEYETFAEYYKTKYNLDLTNLNQPLLDVDHTSSRLNLL 1000
1001 TPRHLNQKGKALPLSSAEKRKAKWESLQNKQILVPELCAIHPIPASLWRK 1050
1051 AVCLPSILYRLHCLLTAEELRAQTASDAGVGVRSLPVDFRYPNLDFGWKK 1100
1101 SIDSKSFISTCNSSLAESDNYCKHSTTVVPEHAAHQGATRPSLENHDQMS 1150
1151 VNCKRLPAESPAKLQSEVSTDLTAINGLSYNKNLANGSYDLVNRDFCQGN 1200
1201 QLNYFKQEIPVQPTTSYPIQNLYNYENQPKPSNECPLLSNTYLDGNANTS 1250
1251 TSDGSPAVSTMPAMMNAVKALKDRMDSEQSPSVGYSSRTLGPNPGLILQA 1300
1301 LTLSNASDGFNLERLEMLGDSFLKHAITTYLFCTYPDAHEGRLSYMRSKK 1350
1351 VSNCNLYRLGKKKGLPSRMVVSIFDPPVNWLPPGYVVNQDKSNSEKWEKD 1400
1401 EMTKDCLLANGKLGEACEEEEDLTWRAPKEEAEDEDDFLEYDQEHIQFID 1450
1451 SMLMGSGAFVRKISLSPFSASDSAYEWKMPKKASLGSMPFASGLEDFDYS 1500
1501 SWDAMCYLDPSKAVEEDDFVVGFWNPSEENCGVDTGKQSISYDLHTEQCI 1550
1551 ADKSIADCVEALLGCYLTSCGERAAQLFLCSLGLKVLPVIKRTSREKALD 1600
1601 PAQENGSSQQKSLSGSCAAPVGPRSSAGKDLEYGCLKIPPRCMFDHPDAE 1650
1651 KTLNHLISGFETFEKKINYRFKNKAYLLQAFTHASYHYNTITDCYQRLEF 1700
1701 LGDAILDYLITKHLYEDPRQHSPGVLTDLRSALVNNTIFASLAVKYDYHK 1750
1751 YFKAVSPELFHVIDDFVKFQLEKNEMQGMDSELRRSEEDEEKEEDIEVPK 1800
1801 AMGDIFESLAGAIYMDSGMSLEVVWQVYYPMMQPLIEKFSANVPRSPVRE 1850
1851 LLEMEPETAKFSPAERTYDGKVRVTVEVVGKGKFKGVGRSYRIAKSAAAR 1900
1901 RALRSLKANQPQVPNS 1916
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
What does the NucPred score mean?
| You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper. |
| NucPred score threshold | Specificity | Sensitivity |
| see above | fraction of proteins predicted to be nuclear that actually are nuclear | fraction of true nuclear proteins that are predicted (coverage) |
| 0.10 | 0.45 | 0.88 |
| 0.20 | 0.52 | 0.83 |
| 0.30 | 0.57 | 0.77 |
| 0.40 | 0.63 | 0.69 |
| 0.50 | 0.70 | 0.62 |
| 0.60 | 0.71 | 0.53 |
| 0.70 | 0.81 | 0.44 |
| 0.80 | 0.84 | 0.32 |
| 0.90 | 0.88 | 0.21 |
| 1.00 | 1.00 | 0.02 |
| Sequences which score >= 0.8 with NucPred and which
are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.) |
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